Factor Analysis in Medical Imaging

1. A method for estimating kinetic parameters from image data, the method comprising: using a processor for executing instructions for, providing a model of kinetic contributions from first and second physiological regions; grouping voxels of the image data into first and second groups; determining an average value of the factors associated with the first group, the factors corresponding to blood-flow time activity curves; incorporating the average value into the model; estimating the kinetic parameters based on the model; determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest; and selecting, from ungrouped voxels, a first predefined number of ungrouped voxels that are located nearest to the first seed voxel; and wherein grouping voxels of the image data into the first group comprises defining a first group that includes the selected ungrouped voxels and the first seed voxel.

2. The method of claim 1 , further comprising providing input functions to the model, the input functions comprising factors determined for the first and second physiological regions.

3. The method of claim 1 , further comprising reducing a vector space spanned by the voxels to a subspace within the vector space, the subspace being defined by principal vectors of the voxels.

4. The method of claim 1 , further comprising: determining a second seed voxel for which a sum of distances between the second seed voxel and other voxels of the image data is greatest, the other voxels being remaining ungrouped voxels; selecting, from the remaining ungrouped voxels, a second predefined number of ungrouped voxels that are located nearest to the second seed voxel; and wherein grouping voxels of the image data into the second group comprises defining a second group that includes the selected remaining ungrouped voxels and the second seed voxel.

5. The method of claim 4 , further comprising selecting the first predefined number to be equal to the second predefined number.

6. The method of claim 1 , further comprising: determining ungrouped voxels located within a minimum distance from the first seed voxel; and wherein grouping voxels of the image data into the first group comprises grouping the ungrouped voxels and the first seed voxel.

7. The method of claim 1 , wherein providing the model comprises selecting the model to be a two-compartment model of myocardial factors and of kinetic contributions from a ventricle and a right ventricle; and wherein estimating the kinetic parameters comprises determining extraction and egress rates of transport between myocardial tissue and freely diffusible space.

8. A method for estimating kinetic parameters from image data, the method comprising: using a processor for executing instruction for, providing a model of kinetic contributions from first and second physiological regions; determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest; selecting, from ungrouped voxels, a first predefined number of ungrouped voxels that are located nearest to the first seed voxel; grouping voxels of the image data into first and second groups, wherein the first group includes the selected ungrouped voxels and the first seed voxel; determining an average value of the factors associated with the first group; incorporating the average value into the model; and estimating the kinetic parameters based on the model.

9. The method of claim 8 , further comprising: determining a second seed voxel for which a sum of distances between the second seed voxel and other voxels of the image data is greatest, the other voxels being remaining ungrouped voxels; selecting, from the remaining ungrouped voxels, a second predefined number of ungrouped voxels that are located nearest to the second seed voxel; and wherein grouping voxels of the image data into the second group comprises defining a second group that includes the selected remaining ungrouped voxels and the second seed voxel.

10. The method of claim 9 , further comprising selecting the first predefined number to be equal to the second predefined number.

11. A method for estimating kinetic parameters from image data, the method comprising: using a processor for executing instructions for, providing a model of kinetic contributions from first and second physiological regions; determining a first seed voxel for which a sum of distances between the first seed voxel and other voxels of the image data is greatest; determining ungrouped voxels located within a minimum distance from the first seed voxel; grouping voxels of the image data into the first group and second groups, wherein the first group includes the selected ungrouped voxels and the first seed voxel; determining an average value of the factors associated with the first group; incorporating the average value into the model; and estimating the kinetic parameters based on the model.

12. The method for estimating kinetic parameters from image data, the method comprising: using a processor for executing instructions for, providing a model of kinetic contributions from first and second physiological regions, wherein providing the model includes selecting the model to be a two-compartment model of myocardial factors and of kinetic contributions from a left ventricle and a right ventricle; grouping voxels of the image data into first and second groups; determining an average value of the factors associated with the first group; incorporating the average value into the model; and estimating the kinetic parameters based on the model, wherein estimating the kinetic parameters includes determining extraction and egress rates of transport between myocardial tissue and freely diffusible space.